OpenAI API Agent Skills

Prepare meeting materials with Notion context and Codex research; use when gathering context, drafting agendas/pre-reads, and tailoring materials to attendees.

Deploy applications to Render by analyzing codebases, generating render.yaml Blueprints, and providing Dashboard deeplinks. Use when the user wants to deploy, host, publish, or set up their application on Render's cloud platform.

Use when the user asks for text-to-speech narration or voiceover, accessibility reads, audio prompts, or batch speech generation via the OpenAI Audio API; run the bundled CLI (`scripts/text_to_speech.py`) with built-in voices and require `OPENAI_API_KEY` for live calls. Custom voice creation is out of scope.

Use when the user asks to generate, remix, poll, list, download, or delete Sora videos via OpenAI\u2019s video API using the bundled CLI (`scripts/sora.py`), including requests like \u201cgenerate AI video,\u201d \u201cSora,\u201d \u201cvideo remix,\u201d \u201cdownload video/thumbnail/spritesheet,\u201d and batch video generation; requires `OPENAI_API_KEY` and Sora API access.

Own your AI. Agents, memory, tools, and identity that live on your Mac. Built purely in Swift. Fully offline. Open source. Download for Mac · Plugin Registry Models are getting cheaper and more interchangeable by the day. What's irreplaceable is the layer around them -- your context, your memory, your tools, your identity. Others keep that layer on their servers. Osaurus keeps it on your machine.

Query OpenAI models directly from Claude using MCP protocol. Add to claudedesktopconfig.json: MIT License

An advanced MCP server that provides intelligent web search capabilities using OpenAI's reasoning models. Perfect for AI assistants that need up-to-date information with smart reasoning capabilities. - 🧠 Reasoning Model Support: Full compatibility with OpenAI's latest reasoning models (gpt-5, gpt-5-mini, gpt-5-nano, o3, o4-mini) - ⚡ Smart Effort Control: Intelligent reasoningeffort defaults based

Token usage tracker for OpenAI, Claude, and Gemini APIs with MCP (Model Context Protocol) support. Pass accurate API costs to your users. - 🎯 Simple Integration - One line to wrap your API client - 📊 Automatic Tracking - No manual token counting - 💰 Accurate Pricing - Up-to-date pricing for all models (2025) - 🔄 Multiple Providers - OpenAI, Claude, and Gemini support - 📈 User Management - Tra

Deploy applications and infrastructure to Cloudflare using Workers, Pages, and related platform services. Use when the user asks to deploy, host, publish, or set up a project on Cloudflare.

This repo contains skills for Claude Code, Codex, and any agent that supports the SKILL.md standard. 1. Create a free account at app.lessie.ai — new accounts include trial credits 2. Install all skills: 3. Restart your agent and run any skill by name Skip the CLI install. Add Lessie as an MCP server instead: - CLI + Skills: npm uninstall -g @lessie/cli && rm -rf ~/.lessie/ ~/.claude/skills/lessie

A multi-model AI orchestration MCP server for automated code review and LLM-powered analysis. Multi-MCP integrates with Claude Code CLI to orchestrate multiple AI models (OpenAI GPT, Anthropic Claude, Google Gemini) for code quality checks, security analysis (OWASP Top 10), and multi-agent consensus. Built on the Model Context Protocol (MCP), this tool enables Python developers and DevOps teams to

The AgentMail Toolkit integrates popular agent frameworks and protocols including OpenAI Agents SDK, Vercel AI SDK, and Model Context Protocol (MCP) with the AgentMail API. See the Python and Node packages for language specific setup and usage.

Multi-agent AI consultation framework for Claude Code via MCP. Get a second (and third) opinion from other LLMs when Claude Code alone isn't enough. Claude Code is powerful, but one brain can miss bugs, overlook edge cases, or get stuck in a local optimum. Critical decisions benefit from diverse perspectives. Concilium runs parallel consultations with multiple LLMs through standard MCP protocol. E

Self-hosted MCP server for your documentation. Index your documentation from across the sources and serve it via the Model Context Protocol (MCP) and REST API. ContextMCP creates a searchable knowledge base from your documentation that AI assistants can query via the Model Context Protocol (MCP). 1. Parse - Extract content from your docs, APIs, and READMEs 2. Chunk - Split into semantic chunks opt

An integration that allows Claude Desktop to monitor and query the operational status of major digital platforms including AI providers, cloud services, and developer tools using the Model Context Protocol (MCP). - Monitor world's most used digital platforms (GitHub, Slack, Discord, etc.) - Track AI providers including OpenRouter, OpenAI, Anthropic, and Gemini - Get detailed status information for

This MCP server allows you to access OpenAI's ChatGPT API directly from Claude Desktop. 📝 Read about why I built this project: I Built an AI That Talks to Other AIs: Demystifying the MCP Hype - Call the ChatGPT API with customisable parameters - Aks Claude and ChatGPT to talk to each other in a long running discussion! - Configure model versions, temperature, and other parameters - Use web search

A Model Context Protocol (MCP) server that lets you seamlessly use OpenAI's models right from Claude. - Direct integration with OpenAI's chat models - Support for multiple models including: - gpt-4o-mini - o1-preview - Simple message passing interface - Basic error handling - Node.js >= 18 (includes npm and npx) - Claude Desktop app - OpenAI API key First, make sure you've got the Claude Desktop a

This skill should be used when users want to train or fine-tune language models using TRL (Transformer Reinforcement Learning) on Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, and model persistence.

English | 简体中文 🧠 The data layer for AI systems. Skill Seekers turns any documentation, GitHub repo, or PDF into structured knowledge assets—ready to power AI Skills (Claude, Gemini, OpenAI), RAG pipelines (LangChain, LlamaIndex, Pinecone), and AI coding assistants (Cursor, Windsurf, Cline) in minutes, not hours. Skill Seekers is the universal preprocessing layer that sits between raw documentatio

MCP Assistant Web-based MCP client for remote servers and AI tool workflows. MCP Assistant addresses common pain points when working with the Model Context Protocol: - Connect to remote MCP servers from one interface - Manage multiple MCP servers from a single interface - Handle OAuth 2.0 and OpenID Connect flows without manual token juggling - Explore available tools and run them directly from th

Expert in building voice AI applications - from real-time voice agents to voice-enabled apps. Covers OpenAI Realtime API, Vapi for voice agents, Deepgram for transcription, ElevenLabs for synthesis, LiveKit for real-time infrastructure, and WebRTC fundamentals. Knows how to build low-latency, production-ready voice experiences. Use when: voice ai, voice agent, speech to text, text to speech, realtime voice.

- A minimal server/client application implementation utilizing the Model Context Protocol (MCP) and Azure OpenAI. 1. The MCP server is built with FastMCP. 2. Playwright is an an open source, end to end testing framework by Microsoft for testing your modern web applications. 3. The MCP response about tools will be converted to the OpenAI function calling format. 4. The bridge that converts the MCP

Build AI applications using Azure AI Projects SDK for JavaScript (@azure/ai-projects). Use when working with Foundry project clients, agents, connections, deployments, datasets, indexes, evaluations, or getting OpenAI clients.

English | 中文 k8m 是一款AI驱动的 Mini Kubernetes AI Dashboard 轻量级控制台工具，专为简化集群管理设计。它基于 AMIS 构建，并通过 kom 作为 Kubernetes API 客户端，k8m 内置了 Qwen2.5-Coder-7B，支持deepseek-ai/DeepSeek-R1-Distill-Qwen-7B模型 模型交互能力，同时支持接入您自己的私有化大模型（包括ollama）。 DEMO-InCluster模式 用户名密码 demo/demo - 详细的配置和使用说明请参考文档。 - 更新日志请参考更新日志。 - 开发设计文档-中文 - 开发设计文档-English - 迷你化设计：所有功能整合在一个单一的可执行文件中，部署便捷，使用简单。 - 简便易用：友好的用户界面和直观的操作流程，让 Kubernetes 管理更加轻松。支持